Metadata-Version: 2.1
Name: lit-nlp
Version: 0.2
Summary: Language Interpretability Tool.
Home-page: https://github.com/pair-code/lit
Author: Google Inc.
License: Apache 2.0
Platform: UNKNOWN
Description-Content-Type: text/markdown
Requires-Dist: absl-py
Requires-Dist: attrs
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: pandas
Requires-Dist: scikit-learn
Requires-Dist: lime
Requires-Dist: sacrebleu
Requires-Dist: umap-learn
Requires-Dist: Werkzeug

# Language Interpretability Tool (LIT)

The Language Interpretability Tool (LIT) is a visual, interactive
model-understanding tool for NLP models.

LIT is built to answer questions such as:

*   **What kind of examples** does my model perform poorly on?
*   **Why did my model make this prediction?** Can this prediction be attributed
    to adversarial behavior, or to undesirable priors in the training set?
*   **Does my model behave consistently** if I change things like textual style,
    verb tense, or pronoun gender?

LIT supports a variety of debugging workflows through a browser-based UI.
Features include:

*   **Local explanations** via salience maps, attention, and rich visualization
    of model predictions.
*   **Aggregate analysis** including custom metrics, slicing and binning, and
    visualization of embedding spaces.
*   **Counterfactual generation** via manual edits or generator plug-ins to
    dynamically create and evaluate new examples.
*   **Side-by-side mode** to compare two or more models, or one model on a pair
    of examples.
*   **Highly extensible** to new model types, including classification,
    regression, span labeling, seq2seq, and language modeling. Supports
    multi-head models and multiple input features out of the box.
*   **Framework-agnostic** and compatible with TensorFlow, PyTorch, and more.

The source code and documentation can be found at https://github.com/pair-code/lit.


